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Record W2317131838 · doi:10.1021/jo300715d

Application of the Systems Chemistry Approach on the Ammonolysis of 1-Ethoxycarbonyl- and 1-Phenoxycarbonyl-3-(2-thienyl)oxindoles. A Method to Predict Reactivity

2012· article· en· W2317131838 on OpenAlexaff
Zoltán Mucsi, Márta Porcs‐Makkay, Gyula Simig, Imre G. Csizmadia, Balázs Volk

Bibliographic record

VenueThe Journal of Organic Chemistry · 2012
Typearticle
Languageen
FieldChemistry
TopicChemical Reaction Mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemistryReactivity (psychology)Computational chemistryMoleculeCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The routine prediction of the reactivity of a complex, multifunctional molecule is a challenging and time-consuming procedure. In the last step of the synthesis of the well-known drug substance tenidap, a nonexpected difference was observed between the reactivities of two closely related carbamate moieties, the N-ethoxycarbonyl and the N-phenoxycarbonyl group. A detailed kinetic study, necessitating a significant computational effort, is described in the present paper for this reaction step. On the other hand, the systems chemistry concept, by analyzing the details of the electronic structure and the connections between functional groups in a fast and simple way, is also able to answer this question using various "-icity" parameters (aromaticity, carbonylicity, olefinicity). The complete systems chemistry approach involves all these conjugativicity parameters, while its further simplified version is based on only one key parameter, which is carbonylicity in the present case. The above methods were compared in terms of their predictive power. The results show that the systems chemistry concept, even its one-parameter version, is applicable for the characterization of this challenging reactivity issue.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.234
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2012
Admission routes1
Has abstractyes

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